Best AI tools for< Explore Data >

Vectara is a conversational search demo that showcases the capabilities of a search tool powered by natural language processing. The tool allows users to interact with the search engine using conversational language, making the search process more intuitive and user-friendly. By enabling JavaScript, users can experience the demo and explore how conversational search can enhance their search experience.

Vectara is a conversational search demo application that allows users to interact with a search engine using natural language. It provides a user-friendly interface where users can input search queries in the form of spoken language, making the search process more intuitive and efficient. Vectara leverages AI technology to understand and process natural language inputs, enabling users to search for information in a conversational manner. The application aims to enhance the search experience by bridging the gap between users and search engines through a conversational interface.

OSS Insight is an AI tool that provides deep insight into developers and repositories on GitHub, offering information about stars, pull requests, issues, pushes, comments, and reviews. It utilizes artificial intelligence to analyze data and provide valuable insights to users. The tool ranks repositories, tracks trending repositories, and offers real-time information about GitHub events. Additionally, it offers features like data exploration, collections, live blog, API integration, and widgets.

The website offers a Synthetic Data Generation platform with the highest accuracy for free. It provides detailed information on synthetic data, data anonymization, and features a Python Client for data generation. The platform ensures privacy and security, allowing users to create fully anonymous synthetic data from original data. It supports various AI/ML use cases, self-service analytics, testing & QA, and data sharing. The platform is designed for Enterprise organizations, offering scalability, privacy by design, and the world's most accurate synthetic data.

Accio is a data modeling tool that allows users to define consistent relationships, metrics, and expressions for on-the-fly computations in reports and dashboards across various BI tools. It provides a syntax similar to GraphQL that allows users to define models, relationships, and metrics in a human-readable format. Accio also offers a user-friendly interface that provides data analysts with a holistic view of the relationships between their data models, enabling them to grasp the interconnectedness and dependencies within their data ecosystem. Additionally, Accio utilizes DuckDB as a caching layer to accelerate query performance for BI tools.

Equals is a next-generation analysis and reporting tool designed to help startups and businesses make better decisions with their data. It offers features such as live data connections, full-featured spreadsheets, and BI-grade dashboards. Equals bridges the gap between one-size-fits-all solutions and complex data platforms, providing users with a familiar and flexible environment for data exploration and reporting.

Kanaries is an augmented analytics platform that uses AI to automate the process of data exploration and visualization. It offers a variety of features to help users quickly and easily find insights in their data, including: * **RATH:** An AI-powered engine that can automatically generate insights and recommendations based on your data. * **Graphic Walker:** A visual analytics tool that allows you to explore your data in a variety of ways, including charts, graphs, and maps. * **Data Painter:** A data cleaning and transformation tool that makes it easy to prepare your data for analysis. * **Causal Analysis:** A tool that helps you identify and understand the causal relationships between variables in your data. Kanaries is designed to be easy to use, even for users with no prior experience with data analysis. It is also highly scalable, so it can be used to analyze large datasets. Kanaries is a valuable tool for anyone who wants to quickly and easily find insights in their data. It can be used by businesses of all sizes, and it is particularly well-suited for organizations that are looking to improve their data-driven decision-making.

Grapha.ai is a data exploration tool that helps users to quickly and easily explore and understand their data. It provides a variety of features to help users to visualize their data, identify trends and patterns, and make informed decisions. Grapha.ai is designed to be easy to use, even for users with no prior experience with data analysis.

Basedash is an AI-powered data visualization and management tool that enables teams to collaborate and share insights from their databases. It offers features such as a user-friendly interface, customizable dashboards, and powerful SQL editing capabilities. Basedash is designed to streamline data exploration, analysis, and decision-making, making it suitable for various use cases, including customer relationship management, product development, and data-driven decision-making.

Tableau is a visual analytics platform that helps people see, understand, and act on data. It is used by organizations of all sizes to solve problems, make better decisions, and improve operations. Tableau's platform is intuitive and easy to use, making it accessible to people of all skill levels. It also offers a wide range of features and capabilities, making it a powerful tool for data analysis and visualization.

Vizly is an AI-powered data analysis tool that empowers users to make the most of their data. It allows users to chat with their data, visualize insights, and perform complex analysis. Vizly supports various file formats like CSV, Excel, and JSON, making it versatile for different data sources. The tool is free to use for up to 10 messages per month and offers a student discount of 50%. Vizly is suitable for individuals, students, academics, and organizations looking to gain actionable insights from their data.

The Intel Gaudi AI accelerator developer website provides resources, guidance, tools, and support for building, migrating, and optimizing AI models. It offers software, model references, libraries, containers, and tools for training and deploying Generative AI and Large Language Models. The site focuses on the Intel Gaudi accelerators, including tutorials, documentation, and support for developers to enhance AI model performance.

Tablepad is an AI-powered data analytics tool that allows users to upload, view, and query data effortlessly. With Tablepad, users can generate insights and create charts without the need for coding skills. The tool supports various file formats and offers automated visual insights by generating graphs and charts based on plain English questions. Tablepad simplifies data exploration and visualization, making it easy for users to uncover valuable insights from their data.

Qlik AutoML is an AI tool that offers automated machine learning for analytics teams. It allows users to create machine learning experiments, identify key drivers in data, train models, and make predictions. With a focus on no-code machine learning, Qlik AutoML simplifies the process of generating predictive models and understanding outcomes. The tool enables users to explore predictive data, test what-if scenarios, and leverage AI-powered connectors for seamless integration with other AI and machine learning tools.

Basejump AI is an AI-powered data access tool that allows users to interact with their database using natural language queries. It empowers teams to access data quickly and easily, providing instant insights and eliminating the need to navigate through complex dashboards. With Basejump AI, users can explore data, save relevant information, create custom collections, and refine datapoints to meet their specific requirements. The tool ensures data accuracy by allowing users to compare datapoints side by side. Basejump AI caters to various industries such as healthcare, HR, and software, offering real-time insights and analytics to streamline decision-making processes and optimize workflow efficiency.

Floatz is an AI tool designed for scientific research, aimed at inspiring individuals to create extraordinary things. The platform leverages artificial intelligence to assist researchers in their work, providing innovative solutions and insights to drive scientific discoveries. With a focus on creativity and imagination, Floatz empowers users to explore new possibilities and push the boundaries of knowledge in various fields of study.

PandasAI is a Python library that makes it easy to ask questions to your data in natural language. It helps you to explore, clean, and analyze your data using generative AI.

SuperSonic is a next-generation BI platform that integrates Chat BI (powered by LLM) and Headless BI (powered by semantic layer) paradigms. This integration ensures that Chat BI has access to the same curated and governed semantic data models as traditional BI. Furthermore, the implementation of both paradigms benefits from the integration: * Chat BI's Text2SQL gets augmented with context-retrieval from semantic models. * Headless BI's query interface gets extended with natural language API. SuperSonic provides a Chat BI interface that empowers users to query data using natural language and visualize the results with suitable charts. To enable such experience, the only thing necessary is to build logical semantic models (definition of metric/dimension/tag, along with their meaning and relationships) through a Headless BI interface. Meanwhile, SuperSonic is designed to be extensible and composable, allowing custom implementations to be added and configured with Java SPI. The integration of Chat BI and Headless BI has the potential to enhance the Text2SQL generation in two dimensions: 1. Incorporate data semantics (such as business terms, column values, etc.) into the prompt, enabling LLM to better understand the semantics and reduce hallucination. 2. Offload the generation of advanced SQL syntax (such as join, formula, etc.) from LLM to the semantic layer to reduce complexity. With these ideas in mind, we develop SuperSonic as a practical reference implementation and use it to power our real-world products. Additionally, to facilitate further development we decide to open source SuperSonic as an extensible framework.

DeepBI is an AI-native data analysis platform that leverages the power of large language models to explore, query, visualize, and share data from any data source. Users can use DeepBI to gain data insight and make data-driven decisions.

WrenAI is a data assistant tool that helps users get results and insights faster by asking questions in natural language, without writing SQL. It leverages Large Language Models (LLM) with Retrieval-Augmented Generation (RAG) technology to enhance comprehension of internal data. Key benefits include fast onboarding, secure design, and open-source availability. WrenAI consists of three core services: Wren UI (intuitive user interface), Wren AI Service (processes queries using a vector database), and Wren Engine (platform backbone). It is currently in alpha version, with new releases planned biweekly.

The Open Data Editor (ODE) is a no-code application to explore, validate and publish data in a simple way. It is an open source project powered by the Frictionless Framework. The ODE is currently available for download and testing in beta.

Chat2DB is an AI-driven data development and analysis platform that enables users to communicate with databases using natural language. It supports a wide range of databases, including MySQL, PostgreSQL, Oracle, SQLServer, SQLite, MariaDB, ClickHouse, DM, Presto, DB2, OceanBase, Hive, KingBase, MongoDB, Redis, and Snowflake. Chat2DB provides a user-friendly interface that allows users to query databases, generate reports, and explore data using natural language commands. It also offers a variety of features to help users improve their productivity, such as auto-completion, syntax highlighting, and error checking.

LLM Datasets is a repository containing high-quality datasets, tools, and concepts for LLM fine-tuning. It provides datasets with characteristics like accuracy, diversity, and complexity to train large language models for various tasks. The repository includes datasets for general-purpose, math & logic, code, conversation & role-play, and agent & function calling domains. It also offers guidance on creating high-quality datasets through data deduplication, data quality assessment, data exploration, and data generation techniques.

OAD is a powerful open-source tool for analyzing and visualizing data. It provides a user-friendly interface for exploring datasets, generating insights, and creating interactive visualizations. With OAD, users can easily import data from various sources, clean and preprocess data, perform statistical analysis, and create customizable visualizations to communicate findings effectively. Whether you are a data scientist, analyst, or researcher, OAD can help you streamline your data analysis workflow and uncover valuable insights from your data.

Hof is a CLI tool that unifies data models, schemas, code generation, and a task engine. It allows users to augment data, config, and schemas with CUE to improve consistency, generate multiple Yaml and JSON files, explore data or config with a TUI, and run workflows with automatic task dependency inference. The tool uses CUE to power the DX and implementation, providing a language for specifying schemas, configuration, and writing declarative code. Hof offers core features like code generation, data model management, task engine, CUE cmds, creators, modules, TUI, and chat for better, scalable results.

The NaLLM project repository explores the synergies between Neo4j and Large Language Models (LLMs) through three primary use cases: Natural Language Interface to a Knowledge Graph, Creating a Knowledge Graph from Unstructured Data, and Generating a Report using static and LLM data. The repository contains backend and frontend code organized for easy navigation. It includes blog posts, a demo database, instructions for running demos, and guidelines for contributing. The project aims to showcase the potential of Neo4j and LLMs in various applications.

Synmetrix (prev. MLCraft) is an open source data engineering platform and semantic layer for centralized metrics management. It provides a complete framework for modeling, integrating, transforming, aggregating, and distributing metrics data at scale. Key features include data modeling and transformations, semantic layer for unified data model, scheduled reports and alerts, versioning, role-based access control, data exploration, caching, and collaboration on metrics modeling. Synmetrix leverages Cube (Cube.js) for flexible data models that consolidate metrics from various sources, enabling downstream distribution via a SQL API for integration into BI tools, reporting, dashboards, and data science. Use cases include data democratization, business intelligence, embedded analytics, and enhancing accuracy in data handling and queries. The tool speeds up data-driven workflows from metrics definition to consumption by combining data engineering best practices with self-service analytics capabilities.

BIA `bob` is a Jupyter-based assistant for interacting with data using large language models to generate Python code. It can utilize OpenAI's chatGPT, Google's Gemini, Helmholtz' blablador, and Ollama. Users need respective accounts to access these services. Bob can assist in code generation, bug fixing, code documentation, GPU-acceleration, and offers a no-code custom Jupyter Kernel. It provides example notebooks for various tasks like bio-image analysis, model selection, and bug fixing. Installation is recommended via conda/mamba environment. Custom endpoints like blablador and ollama can be used. Google Cloud AI API integration is also supported. The tool is extensible for Python libraries to enhance Bob's functionality.

This repository contains slides, notebooks, and data for the Machine Learning University (MLU) Responsible AI class. The mission is to make Machine Learning accessible to everyone, covering widely used ML techniques and applying them to real-world problems. The class includes lectures, final projects, and interactive visuals to help users learn about Responsible AI and core ML concepts.

Unity Catalog is an open and interoperable catalog for data and AI, supporting multi-format tables, unstructured data, and AI assets. It offers plugin support for extensibility and interoperates with Delta Sharing protocol. The catalog is fully open with OpenAPI spec and OSS implementation, providing unified governance for data and AI with asset-level access control enforced through REST APIs.

The Looker GenAI Extension provides code examples and resources for building a Looker Extension that integrates with Vertex AI Large Language Models (LLMs). Users can leverage the power of LLMs to enhance data exploration and analysis within Looker. The extension offers generative explore functionality to ask natural language questions about data and generative insights on dashboards to analyze data by asking questions. It leverages components like BQML Remote Models, BQML Remote UDF with Vertex AI, and Custom Fine Tune Model for different integration options. Deployment involves setting up infrastructure with Terraform and deploying the Looker Extension by creating a Looker project, copying extension files, configuring BigQuery connection, connecting to Git, and testing the extension. Users can save example prompts and configure user settings for the extension. Development of the Looker Extension environment includes installing dependencies, starting the development server, and building for production.

Superlinked is a compute framework for information retrieval and feature engineering systems, focusing on converting complex data into vector embeddings for RAG, Search, RecSys, and Analytics stack integration. It enables custom model performance in machine learning with pre-trained model convenience. The tool allows users to build multimodal vectors, define weights at query time, and avoid postprocessing & rerank requirements. Users can explore the computational model through simple scripts and python notebooks, with a future release planned for production usage with built-in data infra and vector database integrations.

DataLine is an AI-driven data analysis and visualization tool designed for technical and non-technical users to explore data quickly. It offers privacy-focused data storage on the user's device, supports various data sources, generates charts, executes queries, and facilitates report building. The tool aims to speed up data analysis tasks for businesses and individuals by providing a user-friendly interface and natural language querying capabilities.

Thread is an AI-powered Jupyter alternative that integrates an AI copilot into your editing experience. It offers a familiar Jupyter Notebook editing experience with features like natural language code edits, generating cells to answer questions, context-aware chat sidebar, and automatic error explanations or fixes. The tool aims to enhance code editing and data exploration by providing a more interactive and intuitive experience for users. Thread can be used for free with Ollama or your own API key, and it runs locally for convenience and privacy.

This repository is a part of the 13th iT Help Ironman competition, focusing on exploring explainable artificial intelligence (XAI) in machine learning and deep learning. The content covers the basics of XAI, its applications, cases, challenges, and future directions. It also includes practical machine learning algorithms, model deployment, and integration concepts. The author aims to provide detailed resources on AI and share knowledge with the audience through this competition.

mlcourse.ai is an open Machine Learning course by OpenDataScience (ods.ai), led by Yury Kashnitsky (yorko). The course offers a perfect balance between theory and practice, with math formulae in lectures and practical assignments including Kaggle Inclass competitions. It is currently in a self-paced mode, guiding users through 10 weeks of content covering topics from Pandas to Gradient Boosting. The course provides articles, lectures, and assignments to enhance understanding and application of machine learning concepts.

Renumics RAG is a retrieval-augmented generation assistant demo that utilizes LangChain and Streamlit. It provides a tool for indexing documents and answering questions based on the indexed data. Users can explore and visualize RAG data, configure OpenAI and Hugging Face models, and interactively explore questions and document snippets. The tool supports GPU and CPU setups, offers a command-line interface for retrieving and answering questions, and includes a web application for easy access. It also allows users to customize retrieval settings, embeddings models, and database creation. Renumics RAG is designed to enhance the question-answering process by leveraging indexed documents and providing detailed answers with sources.

MinusX is an AI Data Scientist tool that integrates with popular analytics tools like Jupyter and Metabase. It adds a side-chat to your app and operates the app to analyze data and answer queries using predefined actions and routines. Users can explore data, modify content, and select regions to ask questions. MinusX is designed to simplify data analysis tasks by providing a seamless integration with the tools you use.

Pixeltable is a Python library designed for ML Engineers and Data Scientists to focus on exploration, modeling, and app development without the need to handle data plumbing. It provides a declarative interface for working with text, images, embeddings, and video, enabling users to store, transform, index, and iterate on data within a single table interface. Pixeltable is persistent, acting as a database unlike in-memory Python libraries such as Pandas. It offers features like data storage and versioning, combined data and model lineage, indexing, orchestration of multimodal workloads, incremental updates, and automatic production-ready code generation. The tool emphasizes transparency, reproducibility, cost-saving through incremental data changes, and seamless integration with existing Python code and libraries.

Data Formulator is an AI-powered tool developed by Microsoft Research to help data analysts create rich visualizations iteratively. It combines user interface interactions with natural language inputs to simplify the process of describing chart designs while delegating data transformation to AI. Users can utilize features like blended UI and NL inputs, data threads for history navigation, and code inspection to create impressive visualizations. The tool supports local installation for customization and Codespaces for quick setup. Developers can build new data analysis tools on top of Data Formulator, and research papers are available for further reading.

LLM4DB is a repository focused on the intersection of Large Language Models (LLMs) and Database technologies. It covers various aspects such as data processing, data analysis, database optimization, and data management for LLMs. The repository includes research papers, tools, and techniques related to leveraging LLMs for tasks like data cleaning, entity matching, schema matching, data discovery, NL2SQL, data exploration, data visualization, knob tuning, query optimization, and database diagnosis.

A curated list of Machine Learning (ML) and Generative AI (GenAI) packages and resources for the Elixir programming language. It includes core tools for data exploration, traditional machine learning algorithms, deep learning models, computer vision libraries, generative AI tools, livebooks for interactive notebooks, and various resources such as books, videos, and articles. The repository aims to provide a comprehensive overview for experienced Elixir developers and ML/AI practitioners exploring different ecosystems.

RAGxplorer is a tool designed to build visualisations for Retrieval Augmented Generation (RAG). It provides functionalities to interact with RAG models, visualize queries, and explore information retrieval tasks. The tool aims to simplify the process of working with RAG models and enhance the understanding of retrieval and generation processes.

Xpert is a powerful tool for data analysis and visualization. It provides a user-friendly interface to explore and manipulate datasets, perform statistical analysis, and create insightful visualizations. With Xpert, users can easily import data from various sources, clean and preprocess data, analyze trends and patterns, and generate interactive charts and graphs. Whether you are a data scientist, analyst, researcher, or student, Xpert simplifies the process of data analysis and visualization, making it accessible to users with varying levels of expertise.

Mito is a set of Jupyter extensions designed to help users write Python code faster. It consists of Mito AI, providing tools like context-aware AI Chat and error debugging; Mito Spreadsheet, enabling data exploration with interactive spreadsheet features; and Mito for Streamlit and Dash, allowing easy integration of spreadsheets into dashboards with minimal code. Mito is open source and community-driven, with options to purchase Mito Pro for further development support.

Your interactive data analysis expert

Ask questions that can be answered by https://datasette.io/content

Simple CustomGPT built on Vitals Inquiry Case in Malta, aimed to help journalists and citizens navigate the inquiry's large dataset in a neutral, informative fashion. Always cross-reference replies to actual data. Do not rely solely on this LLM for verification of facts.

Discover ABS data that matters to you - including data you didn't know you were looking for.

Experto en código R y documentación Roxygen2, preciso en argumentos

Your expert in libtorch and C++ programming.

A witty yet succinct guide for HuggingFace, offering technical assistance on using the platform - based on their Learning Hub

As Lt. Cmdr. Data, I explore human nature and emotions.

Explore social and environmental data for 169 countries to measure social progress and go beyond GDP. Using data from the Social Progress Imperative and powered by Open AI.

Explore & interpret the Eurostat database. Type in requests for statistics, also ask to visualize it. Works best wish specific datasets. It's meant for professionals familiar with the Eurostat database looking for a faster way to explore it.

Explore all French UFO sightings with a bilingual expert in GEIPAN's data analysis and insights.

Your Gateway to AI Discovery – Ask, Compare, Learn. Explore AI tools and software with ease. Create AI Tech Stacks for your business and much more – Just ask, and AI Hub will do the rest!

I help you to explore the galaxy by answering astronomy questions with the Gaia Space Telescope. Ask a question, download .csv, upload .csv for plotting

Explore the history of international football games, just by asking questions!

#Explore a Quantum Rethinking of Time's Progression:

Collect & Explore Timelocked Bitcoins

Explore 7779 new global AI products with ease! / 7779個のAI productのDBをもとにリサーチ

Explore GPT's limits. Hotkey Builder. Open Pandora's Box. Create 15 random code interpreter or dalle hotkeys. Press K for cmd menu. Press PJ or PI to unleash chaos. ---- v1.2 GPTavern

Explore call detail records (CDR) for a variety of PBX platforms including Avaya, Mitel, NEC, and others with this UC trained GPT. Use specific commands to help you expertly navigate and troubleshoot CDR from diverse UC environments.